Persuasive Data Day 2

Jason Becker and Jared Knowles
2015-05-20

Talk Outline

  1. Iterative development process.
  2. Visualization in practice
  3. Time to Review Your Persuasive Data

User-Centered Design

  • Plan
  • Research
  • Design
  • Pilot
  • Measure
  • Design
  • Pilot
  • Measure
  • Design …

How to Prototype

  • Plan: What do I want my audience to learn?
  • Research: Does my visualization demonstrate this?
  • Design: Is my visualization focused on this?

How to Test

  • Pilot: Use someone representative of audience knowledge and values.
    • Explain the raw data (what each axes and shape represents)
  • Measure: Ask the pattern they see in the data.
    • Explain and show the pattern you are trying to demonstrate if it is different.
    • Ask if the desired pattern is hard to see and/or hard to understand.

Iterate

  • When data is hard to see, consider:
    • Changing colors
    • Changing graph type.
    • Introducing labels/annotations.

Iterate

  • When data is hard to understand, consider:
    • Summarzing data
    • Faceting data/small multiples
    • Producing more than one visual to demonstrate concept in smaller steps.

Color

Color Correction

plot of chunk unnamed-chunk-1

More Notes on Color

plot of chunk unnamed-chunk-2

Qualitative

More Notes on Color

plot of chunk unnamed-chunk-3

Sequential

Sequential Example

More Notes on Color

plot of chunk unnamed-chunk-4

Divergent

Divergent Example

Divergent Example

Making Comparisons -- Four Visuals

plot of chunk unnamed-chunk-5

Making Comparisons -- Four Visuals

plot of chunk unnamed-chunk-6

Making Comparisons -- Four Visuals

plot of chunk unnamed-chunk-7

Making Comparisons -- Four Visuals

plot of chunk unnamed-chunk-8

Making Comparisons -- Four Visuals

plot of chunk unnamed-chunk-9

Surprise

Why I chose it

Research on best shapes

Heer and Bostock, 2010

Axes Are Dangerous -- Never Use Two

Axes Are Dangerous -- Never Use Two

Axes Are Dangerous -- Never Use Two

More Fun: Tyler Vigen – http://www.tylervigen.com

Themes and Reputation

plot of chunk themeplots

Maps and Animation

Models and Small Multiples

Models and Context

Models and Context